AIMC Topic: Magnetic Resonance Imaging
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Circumventing the curse of dimensionality in magnetic resonance fingerprinting through a deep learning approach.
NMR in biomedicine
Jan 27, 2022
Magnetic resonance fingerprinting (MRF) is a rapidly developing approach for fast quantitative MRI. A typical drawback of dictionary-based MRF is an explosion of the dictionary size as a function of the number of reconstructed parameters, according t...
Investigating Simultaneity for Deep Learning-Enhanced Actual Ultra-Low-Dose Amyloid PET/MR Imaging.
AJNR. American journal of neuroradiology
Jan 27, 2022
BACKGROUND AND PURPOSE: Diagnostic-quality amyloid PET images can be created with deep learning using actual ultra-low-dose PET images and simultaneous structural MR imaging. Here, we investigated whether simultaneity is required; if not, MR imaging-...
Classification of brain tumours in MR images using deep spatiospatial models.
Scientific reports
Jan 27, 2022
A brain tumour is a mass or cluster of abnormal cells in the brain, which has the possibility of becoming life-threatening because of its ability to invade neighbouring tissues and also form metastases. An accurate diagnosis is essential for successf...
A Deep Learning Approach for MRI in the Diagnosis of Labral Injuries of the Hip Joint.
Journal of magnetic resonance imaging : JMRI
Jan 26, 2022
BACKGROUND: The diagnosis of labral injury on MRI is time-consuming and potential for incorrect diagnoses.
Automatic deep learning multicontrast corpus callosum segmentation in multiple sclerosis.
Journal of neuroimaging : official journal of the American Society of Neuroimaging
Jan 26, 2022
BACKGROUND AND PURPOSE: Corpus callosum (CC) atrophy is predictive of future disability in multiple sclerosis (MS). However, current segmentation methods are either labor- or computationally intensive. We therefore developed an automated deep learnin...
Attention-guided deep learning for gestational age prediction using fetal brain MRI.
Scientific reports
Jan 26, 2022
Magnetic resonance imaging offers unrivaled visualization of the fetal brain, forming the basis for establishing age-specific morphologic milestones. However, gauging age-appropriate neural development remains a difficult task due to the constantly c...
Brain tumour classification of magnetic resonance images using a novel CNN-based medical image analysis and detection network in comparison to VGG16.
Journal of population therapeutics and clinical pharmacology = Journal de la therapeutique des populations et de la pharmacologie clinique
Jan 26, 2022
AIM: This study aims at developing an automatic medical image analysis and detection for accurate classification of brain tumors from MRI dataset. The study implemented our novel MIDNet18 CNN architecture in comparison with the VGG16 CNN architecture...
A self-supervised domain-general learning framework for human ventral stream representation.
Nature communications
Jan 25, 2022
Anterior regions of the ventral visual stream encode substantial information about object categories. Are top-down category-level forces critical for arriving at this representation, or can this representation be formed purely through domain-general ...
MDReg-Net: Multi-resolution diffeomorphic image registration using fully convolutional networks with deep self-supervision.
Human brain mapping
Jan 24, 2022
We present a diffeomorphic image registration algorithm to learn spatial transformations between pairs of images to be registered using fully convolutional networks (FCNs) under a self-supervised learning setting. Particularly, a deep neural network ...
Editorial for "An Unsupervised Deep Learning Approach for Dynamic-Exponential Intravoxel Incoherent Motion MRI Modeling and Parameter Estimation in the Liver".
Journal of magnetic resonance imaging : JMRI
Jan 21, 2022
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